Rpatton: // via Wikitext Extension for VSCode

2025-04-17T21:37:02Z

// via Wikitext Extension for VSCode

← Older revision		Revision as of 16:37, 17 April 2025
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	Text data is critically important for most everything you do in Grooper. The '''Recognize''' activity obtains text data from both scanned (or otherwise image-based) documents and digital documents with native machine-readable text already embedded. For image-based documents, the activity will execute an [[image:GrooperIcon_OCRProfile.png]] '''[[OCR Profile]]''', performing [[OCR]] according to its settings. For digital documents, the activity will extract the embedded text.		Text data is critically important for most everything you do in Grooper. The '''Recognize''' activity obtains text data from both scanned (or otherwise image-based) documents and digital documents with native machine-readable text already embedded. For image-based documents, the activity will execute an [[image:GrooperIcon_OCRProfile.png]] '''[[OCR Profile]]''', performing [[OCR]] according to its settings. For digital documents, the activity will extract the embedded text.

	'''Recognize''' can also locate and store ~~any~~ layout data ~~obtained from~~ a ~~referenced~~ [[image:GrooperIcon_IPProfile.png]] '''[[IP Profile]]''' using '''[[IP Command]]s''' such as '''Line Detection''' or '''Box Detection''' .		'''Recognize''' can also locate and store layout data on a document. To do so, an [[image:GrooperIcon_IPProfile.png]] '''[[IP Profile]]''' using '''[[IP Command]]s''' such as '''Line Detection''' or '''Box Detection''' must be referenced.

	The '''''Recognize''''' activity can:		The '''''Recognize''''' activity can:
	# get machine readable text from images by performing OCR on a page or embedded images in a PDF,		# get machine readable text from images by performing OCR on a page or embedded images in a PDF
	# extract native ~~PDF~~ text directly		# extract native text attached to a document directly
	# extract [[Layout Data]] or		# extract [[Layout Data]] with a referenced '''IP Profile'''
	# any combination at the document folder or page level.		# any combination of the above at the document folder or page level

	'''''Recognize''''' is useful in all cases when a document needs text rendered readable to '''Grooper''', either from a native electronic format or via OCR from an image or scan~~. '''''Recognize''''' represents a simplified metaphor for gathering information (text and layout) from documents~~. '''''Recognize''''' is a backbone activity for most other use cases in '''Grooper'''.		'''''Recognize''''' is useful in all cases when a document needs text rendered readable to '''Grooper''', either from a native electronic format or via OCR from an image or scan. '''''Recognize''''' is a backbone activity for most other use cases in '''Grooper'''.

	Below is an example of an image processed by the '''''Recognize''''' activity and its results.		Below is an example of an image processed by the '''''Recognize''''' activity and its results.

Dgreenwood at 15:07, 2 March 2025

2025-03-02T15:07:50Z

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			[[image:2023_Recognize_01_About_01.png\|frame\|The Recognize activity's property panel.]]

			<blockquote>{{#lst:Glossary\|Recognize}}</blockquote>

			{\|cellpadding="10" cellspacing="5"
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			You may download and import the file(s) below into your own Grooper environment (version 2023.1). There is a '''[[Batch]]''' with the example document(s) discussed in this tutorial, as well as a '''[[Project]]''' configured according to its instructions.
			<br>
			* [[Media:2023.1_Wiki_Recognize_Batch.zip]]
			* [[Media:2023.1_Wiki_Recognize_Project.zip]]
			\|}
			<br clear=all>
			== About ==
			Text data is critically important for most everything you do in Grooper. The '''Recognize''' activity obtains text data from both scanned (or otherwise image-based) documents and digital documents with native machine-readable text already embedded. For image-based documents, the activity will execute an [[image:GrooperIcon_OCRProfile.png]] '''[[OCR Profile]]''', performing [[OCR]] according to its settings. For digital documents, the activity will extract the embedded text.

			'''Recognize''' can also locate and store any layout data obtained from a referenced [[image:GrooperIcon_IPProfile.png]] '''[[IP Profile]]''' using '''[[IP Command]]s''' such as '''Line Detection''' or '''Box Detection''' .

			The '''''Recognize''''' activity can:
			# get machine readable text from images by performing OCR on a page or embedded images in a PDF,
			# extract native PDF text directly
			# extract [[Layout Data]] or
			# any combination at the document folder or page level.

			'''''Recognize''''' is useful in all cases when a document needs text rendered readable to '''Grooper''', either from a native electronic format or via OCR from an image or scan. '''''Recognize''''' represents a simplified metaphor for gathering information (text and layout) from documents. '''''Recognize''''' is a backbone activity for most other use cases in '''Grooper'''.

			Below is an example of an image processed by the '''''Recognize''''' activity and its results.

			=== Image ===
			This is the original image after being run through the '''''Recognize''''' activity. The highlighted portions are text segments the '''OCR Profile''' identified and captured text data from. You can view OCR and extracted PDF text by right-clicking a page or folder in a [[image:GrooperIcon_Batch.png]] '''[[Batch]]''' (depending on which level the activity ran), selecting "Item Properties" and pressing the ellipsis button at the end of the '''''Results''''' property.

			[[image:2023_Recognize_01_About_02.png]]

			=== Layout View ===
			This is the character results displayed in a "layout view". The layout view is a visual representation mimicking the document's structure from the image, using the text data and their character positions obtained from the '''''Recognize''''' activity.

			[[image:2023_Recognize_01_About_03.png]]

			=== Text Data ===
			This is a "text view" of the extracted text from OCR during the '''''Recognize''''' activity. This text will be used to separate pages into documents, classify documents according to how they are defined in a [[image:GrooperIcon_ContentModel.png]] '''[[Content Model]]''', extract [[image:GrooperIcon_DataField.png]] '''[[Data Field\|Data Fields]]''', or a number of other '''Grooper''' activities using text data.

			[[image:2023_Recognize_01_About_04.png]]

			=== Character Data ===
			This is the individual character data for each character recognized, including character confidence and position information.

			The character data is saved as a .txt file on the associated [[image:GrooperIcon_BatchPage.png]] '''Batch Page''' or [[image:GrooperIcon_BatchFolder.png]] '''Batch Folder''' object, depending at which level the '''''Recognize''''' activity ran.

			[[image:2023_Recognize_01_About_05.png]]

			=== Layout Data ===
			This is the layout information obtained from the activity. Layout information can yield visual information useful to further '''Grooper''' activities, such as whether or not checkboxes on a form are checked, or table line positions for extracting tabular data.

			The layout information is saved as a .json file on the associated '''Batch Page''' or '''Batch Folder''' object, depending at which '''''[[Scope]]''''' the '''''Recognize''''' activity ran.

			[[image:2023_Recognize_01_About_06.png]]

			== How To: Configure the Activity ==
			=== Prereqs ===
			First, you will need to identify your plan of attack by analyzing your documents. Here are a few questions to get you started:

			* '''How are your documents coming into Grooper?'''
			*: Primarily, '''''Recognize''''' is for getting text from documents. If your documents are coming in as image files, such as .tiff, you will need to obtain text through OCR. If you are scanning documents using a physical scanner, this will likely be your route. If you need OCR text, you will also need to create an '''OCR Profile'''. If your documents are coming in as PDFs, you will need to answer a couple more questions.

			* '''Do you have PDF documents with native text embedded in them?'''
			*: If so, you will want to to obtain PDF text through native text extraction. If you have PDF documents that do not have native text embedded, or you do not wish to extract the embedded text because it is inaccurate, you will want to obtain text through OCR. If you need OCR text, you will also need to create an '''OCR Profile'''.

			* '''Do you have PDF documents with images containing text as well as embedded text?'''
			*: If so, you will want to use both OCR and native text extraction.

			* '''Do your documents have layout data, such as table lines, barcodes, and OMR checkboxes, needed to extract data, classify documents, or other document processing activites?'''
			*: If so, you will need to create an '''IP Profile''' containing the associate image feature detection commands, such as Line Detection, Barcode Detection, and Box Detection.

			=== Obtaining OCR Text ===
			If you are processing solely image files, all you need to do is set an '''OCR Profile'''. Select the '''''OCR Profile''''' property of the '''''Recognize''''' activity and expand the dropdown list. Select the desired '''OCR Profile''' from the list.

			[[image:2023_Recognize_01_About_07.png]]


			If your documents are PDFs with image-based content containing text information that is not embedded in the PDF, you will also need to set an '''OCR Profile''' here. Furthermore, under '''''PDF Options''''', you will need to set the '''''OCR Assist''''' property to either ''Auto'' or ''Always''.

			* ''Auto'' will selectively apply OCR to PDF pages containing images.
			* ''Always'' will perform OCR on all pages.

			OCR results are then combined with native text extraction to form a single complete text output for the document.

			[[image:2023_Recognize_01_About_08.png]]

			=== Obtaining PDF Text ===
			To extract native text from PDFs, set the '''''Native Text Extraction''''' property to ''Full'' or ''Simple''.

			* ''Full'' will extract all text from the document, including form fields.
			* ''Simple'' will only extract native text segments.

			[[image:2023_Recognize_01_About_09.png]]

			=== Obtaining Layout Data ===
			Layout data is obtained from image feature detection commands on an '''IP Profile'''. If performing OCR, include an '''IP Profile''' containing these commands using the '''''IP Profile''''' property of the '''OCR Profile'''.

			[[image:2023_Recognize_01_About_10.png]]


			If you are not using OCR, you may set an '''IP Profile''' using the '''''Alternate IP''''' property under the "PDF Options" heading.
			In the image below an '''IP Profile''' named "Layout Data" is referenced, use the "OCR Cleanup" '''IP Profile''' instead if you are using the supplied materials for this article.''

			[[image:2023_Recognize_01_About_11.png]]


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			Layout data may need to be collected on the page level rather than the folder level to avoid problems during data extraction. Before running the Recognize activity, PDFs should be split using the "Split Pages" activity against the document. This will create individual page objects nested under the PDF document folder. Then, Recognize's Scope should be set to "Page" before running.
			\|}

Dgreenwood: Dgreenwood moved page Recognize (Activity) to 2023.1:Recognize (Activity) without leaving a redirect

2025-03-02T15:05:29Z

Dgreenwood moved page Recognize (Activity) to 2023.1:Recognize (Activity) without leaving a redirect

← Older revision	Revision as of 10:05, 2 March 2025
(No difference)

Randallkinard at 16:54, 28 August 2024

2024-08-28T16:54:53Z

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Dgreenwood: Created page with "{{Migrated2023}} {{2023:{{PAGENAME}}}}"

2024-01-02T21:02:39Z

Created page with "{{Migrated2023}} {{2023:{{PAGENAME}}}}"

New page

{{Migrated2023}}
{{2023:{{PAGENAME}}}}

2023.1:Recognize (Activity) - Revision history

Rpatton: // via Wikitext Extension for VSCode

Dgreenwood at 15:07, 2 March 2025

Dgreenwood: Dgreenwood moved page Recognize (Activity) to 2023.1:Recognize (Activity) without leaving a redirect

Randallkinard at 16:54, 28 August 2024

Dgreenwood: Created page with "{{Migrated2023}} {{2023:{{PAGENAME}}}}"